lessons from the best and worst student team experiences: how a teacher can make the difference

http://jme.sagepub.com/Journal of Management Education

http://jme.sagepub.com/content/23/5/467The online version of this article can be found at:

DOI: 10.1177/105256299902300503

1999 23: 467Journal of Management EducationDonald R. Bacon, Kim A. Stewart and William S. Silver

Lessons from the Best and Worst Student Team Experiences: How a Teacher can make the Difference

Published by:

http://www.sagepublications.com

On behalf of:

OBTS Teaching Society for Management Educators

can be found at:Journal of Management EducationAdditional services and information for

http://jme.sagepub.com/cgi/alertsEmail Alerts:

http://jme.sagepub.com/subscriptionsSubscriptions:

http://www.sagepub.com/journalsReprints.navReprints:

http://www.sagepub.com/journalsPermissions.navPermissions:

http://jme.sagepub.com/content/23/5/467.refs.htmlCitations:

What is This?

- Oct 1, 1999Version of Record >>

at TEXAS SOUTHERN UNIVERSITY on November 18, 2014jme.sagepub.comDownloaded from at TEXAS SOUTHERN UNIVERSITY on November 18, 2014jme.sagepub.comDownloaded from

http://jme.sagepub.com/

http://jme.sagepub.com/content/23/5/467

http://www.sagepublications.com

http://www.obts.org/

http://jme.sagepub.com/cgi/alerts

http://jme.sagepub.com/subscriptions

http://www.sagepub.com/journalsReprints.nav

http://www.sagepub.com/journalsPermissions.nav

http://jme.sagepub.com/content/23/5/467.refs.html

http://jme.sagepub.com/content/23/5/467.full.pdf

http://online.sagepub.com/site/sphelp/vorhelp.xhtml



JOURNAL OF MANAGEMENT EDUCATION / October 1999Baconet al. / HOW A TEACHER CAN MAKE THE DIFFERENCE

LESSONS FROM THE BESTAND WORST STUDENT TEAMEXPERIENCES: HOW A TEACHERCAN MAKE THE DIFFERENCE

Donald R. BaconKim A. StewartWilliam S. SilverUniversity of Denver

For as long as formal management education has existed, students haveworked in groups to perform team projects.1 And for about the same amountof time, teachers have wondered about the best way to structure and adminis-ter student teams. This issue has gained greater importance recently as agrowing awareness has emerged about the importance of teams in the work-place (A. R. Cohen, 1993; Hackman, 1990). Formal recommendations havebeen developed on how to effectively create and administer student teams(e.g., Strong & Anderson, 1990). However, to date there has been limitedempirical research on how teacher-controlled factors affect the student teamexperience.

Drawing on earlier theoretical development, the present study takes anapplied approach by focusing on contextual variables that a teacher controlsin administering teams: method of team assignment, team longevity, thegrade weight given to teamwork, the use of peer evaluations, team size, man-agement education, and the quality of the instructions a teacher provides to a

467

Authors’Note: Correspondence should be addressed to Donald R. Bacon, Department of Mar-keting, Daniels College of Business, University of Denver, 101 S. University Blvd., Denver, CO80208; (phone) 303-871-2707; (fax) 303-871-2323; (e-mail) [email protected]. Funding for thisresearch from the Daniels College of Business at the University of Denver is gratefullyacknowledged.

JOURNAL OF MANAGEMENT EDUCATION, Vol. 23 No. 5, October 1999 467-488© 1999 Sage Publications, Inc.

at TEXAS SOUTHERN UNIVERSITY on November 18, 2014jme.sagepub.comDownloaded from


team. To examine these variables, we surveyed 116 MBA students about theirbest and worst student team experiences in their MBA program. Contrastingthese best and worst team experiences, we tested hypotheses related to eachof the contextual variables. Overall, our goal was to provide teachers withactionable, empirically supported recommendations for effectively creatingand administering student teams.

Background and Hypotheses

Almost all of the contextual variables examined here have been studiedpreviously, although most have not been researched in a student teams con-text. We draw on the existing literature with some intuitive extensions todevelop hypotheses for testing.

METHOD OF ASSIGNMENT TO TEAMS

Three approaches to assigning students to teams have been explored in theliterature (Decker, 1995): self-selection, random assignment, and teacherassignment. Self-selection has been recommended by some because it mayoffer higher initial cohesion (Strong & Anderson, 1990), and cohesion hasbeen linked to student team performance (Gosenpud & Washbush, 1991;Jaffe & Nebenzahl, 1990; Wolfe & Box, 1988). Student teams often havevery short longevity, perhaps only a few weeks, and so the initial cohesive-ness that self-selected teams often possess may help these teams to becomeproductive more quickly. Others have suggested that self-selection mayencourage students to take more ownership of group problems (Mello, 1993),motivating students to manage interpersonal conflict more successfully. Inaddition to these benefits of self-selection, we note from our experience thatstudents often ask to work with those they have worked with before in previ-ous classes. It is quite possible that some team-related norms have alreadybeen established among these students, which facilitates productivity.

Self-selection is not without problems, however, including the tendencyfor self-selected teams to be overly homogeneous (Jalajas & Sutton,1984-1985), and thus not offer the advantages that some diversity may pro-vide (Bacon, Stewart, & Stewart-Belle, 1998). Self-selected teams may alsopossess an inadequate skill set, unless measures are taken to constrain self-selection (Mello, 1993). Thus, self-selection trades a possible lack of diver-sity and critical skills for initial cohesiveness and established norms. Thetrade-off may be wise with teams of brief longevity, especially if the influ-ence of unique skills is minimal.

468 JOURNAL OF MANAGEMENT EDUCATION / October 1999



A second and widely used approach is random assignment (e.g., Cook,1981; Quirk, 1989; Vora & Akula, 1978). Though some recommend randomassignment because it seems fair, others have questioned this conclusion,suggesting instead that randomly assigning teams is “just as unfair as ran-domly assigning grades—each student would have the same probability ofgetting an A or an F, regardless of their abilities or efforts” (Bacon et al.,1998, p. 69). Each student begins the class with the same chance of workingwith every other student, but due to the random nature of this approach thefinal team assignments can be quite unbalanced in terms of skills, diversity,and general ability. Random assignment is also not likely to generate teamswith a useful combination of skills, or create groups of students who want towork together. We suspect that whereas some randomly assigned teamswould, by chance, end up with a desirable combination of students, otherswould certainly not, and therefore random assignment would not generallybe associated with good team experiences and may be associated with badexperiences.

A third approach to making team assignments is the teacher-assignedapproach. However, this approach is diffuse (teacher-assignment methodswidely differ in the criteria used for making assignments), can be difficult toimplement, and is thus seldom used (15% of teams at our school and 18% in astudy by Decker, 1995). As the self-selection and random assignmentapproaches currently predominate in business schools and in our sample, wefocus our hypothesis about team assignment on these approaches:

Hypothesis 1a:Best teams will include more self-selected teams than will worstteams.

Hypothesis 1b:Best teams will include fewer randomly assigned teams than willworst teams.

TEAM LONGEVITY

Researchers have suggested that a team moves through distinct phases ofdevelopment as its members work together (Tuckman, 1965; for a review ofteam development stages, see Bettenhausen, 1991). For example, Tuckman(1965) proposes that teams proceed through five stages of development: (a)forming, where members become acquainted with each other and orientthemselves to the team task and the team’s expectations of them; (b) storm-ing, where individual roles and personalities emerge and conflict occursabout the team’s mission, objectives, and task; (c) norming, where team con-flict is resolved, members come to agree on team leadership, roles, andbehavioral norms, and team cohesiveness is established; (d) performing,

Bacon et al. / HOW A TEACHER CAN MAKE THE DIFFERENCE 469



where the team focuses on productive interaction and problem solving tocomplete its task; and (e) adjourning, where members feel a myriad of emo-tions as they experience the dissolution of the team once its mission iscompleted.

Although others have suggested that the progress of team developmentmay not be linear (Gersick, 1989), most agree that teams generally progresswith time. Krayer (1988) has noted that having an established team history isone contributor to team maturity. It is possible, however, that when a teamstays together too long, a loss in effectiveness occurs. Katz (1982) observedthis phenomenon in Research and Development (R&D) teams, and foundthat project performance peaked in the second to fourth year of a team anddropped thereafter. This estimate of optimal team longevity far exceeds thelongevity of a typical student team. Within the limited range of longevity ofstudent teams, more longevity is probably better. Therefore,

Hypothesis 2:Best teams will have worked together longer on average than willworst teams.

WEIGHT OF GRADE GIVEN TO TEAMWORK

Given that performance is influenced by rewards (Steers & Porter, 1991)and rewards for students come primarily in the form of grades, we expect thatstudents will perform better on those elements of the course that have greaterimpact on the final course grade. If the percentage of the course grade associ-ated with teamwork is quite low, students may neglect their teamwork alto-gether (e.g., LeRosen, 1976). We hypothesize that

Hypothesis 3:Best teams will have a higher percentage of the course grade associ-ated with teamwork than will worst teams.

PEER EVALUATIONS

In laboratory settings, researchers have often observed that individualstend to reduce their effort when working in a team, a phenomenon referred toas social loafing (Ingham, Levinger, Graves, & Peckham, 1974; Latané, Wil-liams, & Harkins, 1979). Many instructors recommend peer evaluations as away to reduce social loafing in student teams (Mello, 1993; Strong & Ander-son, 1990; Williams, Beard, & Rymer, 1991). Team members are thought tosocial loaf, or free ride, when they perceive that the net benefits (rewards lesscosts) of free riding exceed the net benefits of contributing their fair share(Albanese & Van Fleet, 1985). Therefore, one way to reduce free riding is toreduce the behavior’s net benefits. Peer evaluations are often used to do so by




identifying free riders and then reducing their grades for teamwork(rewards). Peer evaluations can sensitize students to the potential for reducedbenefits and therefore encourage them to contribute fully to the group effort.Some empirical support for this approach is provided by Harkins and Jackson(1985). In a brainstorming task experiment, individual performance wasfound to improve when the subjects believed that their own contributionwould be identifiable.

There is some evidence that peer evaluation may negatively affect a team.The integration of peer evaluations into team project or course grades createsa hybrid reward system, wherein the individual receives rewards based onboth individual and team performance (Wageman, 1995). Rosenbaum et al.(1980) found that such mixed reward systems were associated with poor teamperformance when the team was given a highly interdependent task. Wage-man’s (1995) findings concur, but highlight how reward systems may affectmotivation more than cooperation. Wageman recommends that the rewardsystem be tailored to the task structure: independent tasks should be associ-ated with individual rewards and team/interdependent tasks with teamrewards. The tasks our MBA teams worked on included some mixed tasksand some highly interdependent tasks. Thus, peer evaluations might nega-tively affect some teams. However, the peer evaluation processes commonlyused at our school are not a zero-sum game—that is, all team members couldreceive the maximum reward. This may neutralize the potential negativeeffect of the hybrid reward system.

To date, there is only limited empirical evidence supporting the effective-ness of peer evaluations in student teams, and calls have been made for moreresearch in this area (Michaelsen, 1991). Cook (1981) found the performanceof his graduate sample was substantially higher among the peer evaluationteams, but the performance differences were negligible among the under-graduate teams. It should be noted, however, that Cook’s samples were verysmall (4 graduate teams and 14 undergraduate teams in total), and no statisti-cal tests were performed. In Strong and Anderson’s (1990) study of studentopinions about free riding, students indicated that they believed that peerevaluations do reduce free riding, but they rated other factors—includinggroup cohesiveness, small team size, the option to divorce a team member, orthe option to leave a team—as having a stronger effect on reducing free riding.

Obviously, peer evaluation could be conducted in a variety of ways, butour test of the effects of peer evaluation on team experiences is limited to theevaluation process used at our school. Through many discussions with otherfaculty, it appears that the modal process involves confidential, end-of-the-term-only peer evaluation, and that the evaluation may involve rating scalesand/or open-ended questions. This general approach is common in the




literature (e.g., Clark, 1989; Cook, 1981; LeRosen, 1976, Mello, 1993;Quirk, 1989; Williams et al., 1991), although some suggest a midtermevaluation be used as well. In this article, we will refer to confidential, end-of-the-term-only peer evaluations as the traditional approach to peer evalua-tion. In light of the positive, though limited, support for traditional peerevaluation in the literature, we hypothesize that

Hypothesis 4:A larger percentage of best teams will report using traditional (con-fidential, end-of-the-term-only) peer evaluations than will worst teams.

TEAM SIZE

There is clear consensus in the literature about team size—keep teams assmall as possible (Comer, 1995; Strong & Anderson, 1990). The rationale forthis rule follows from social loafing theory. Latané et al. (1979) describe anumber of problems that teams face as size increases, all of which comeunder the general heading of social loafing. Team performance may declinesimply because of the difficulty in coordinating the efforts of a larger numberof people (coordination losses). Individual effort may decline because indi-viduals feel that their contributions are not identifiable, and therefore theywill not get caught if they reduce their effort (see also Kerr, 1983). Individualsmay also feel that others on the team will do the work better than they will andso, feeling dispensable to the team, they reduce their effort (see also Kerr &Bruun, 1983). Gentry (1980) noted that dissension among team membersincreased with team size, especially among sizes of four or more. Bacon et al.(1998) and Gentry (1980) both noted that team performance did not decreasewith increases in team size, but we suspect that the student’s perception of thequality of the team experience did. Thus, for these reasons, we hypothesize that

Hypothesis 5:The average team size on best teams will be smaller than the averageteam size on worst teams.

MANAGEMENT EDUCATION

The assumption that team training improves team performance is funda-mental in the team literature. When teams do not work well, insufficient teamtraining is often the first suspect (Zemke, 1993). Researchers generally nolonger concern themselves with the question of whether team training iseffective, but instead have moved on to develop a wide variety of team train-ing methods, including methods for managing conflict (e.g., Schultz &Anderson, 1984) and case methods and exercises for training student teams(Fisher, Shaw, & Ryder, 1994; Lerner, 1995; Mesch, 1991). We know of only




one study (Eden, 1985) that found that team training was unrelated to teamperformance.

In our MBA program (like many others), team training is not part of everyclass where teams are used. Instead, early in their program, the students taketwo management classes (4 credit hours each) where team concepts aretaught, along with leadership and other management concepts. As team con-cepts are covered in the class, we would expect that the team experiences stu-dents have after completing both these courses might be improved because ofthe team knowledge gained. Although these courses do not constitute anintensive form of team training, we suspect that this approach to teachingMBAs about teams is common practice, and therefore leads to a very relevanthypothesis:

Hypothesis 6:Among the best teams, the percentage of those who have completedtheir basic management courses will be higher than among the worst teams.

TEAM INSTRUCTIONS

Several researchers have suggested that having a clear team vision (e.g.,Burningham & West, 1995) or at least a clear understanding of team objec-tives (e.g., Fowler, 1995) is important to team success. When team objectivesare unclear, team members may argue over what the team should be doing. Ifan educational objective for the team is for students to experience and resolvetask conflict, this conflict may be constructive (Witteman, 1991). If, however,the instructor has very clear ideas about what the team should produce and howthe team should go about the necessary tasks, but these instructions are notcommunicated to the students, task conflict may be dysfunctional in that itwastes group time in an unnecessary process. We therefore hypothesize that

Hypothesis 7a:Best teams will be more likely to say the instructor gave them suffi-cient instructions on outcomes (what the team was to submit or present) thanwill worst teams.

Hypothesis 7b:Best teams will be more likely to say the instructor gave them suffi-cient instructions on process (how the team should perform its tasks) than willworst teams.

Method

The present research focuses on contextual variables, and how these vari-ables are associated with good and bad team experiences. We used an in-classsurvey methodology to test our hypotheses. The final survey was developedbased on our review of the literature and a pretest survey.




INSTRUMENT

The survey instrument used for hypothesis testing comprised four sec-tions. The first section contained questions used to obtain descriptive statis-tics such as the percentage of teams using peer evaluations or the percentageof teams that were self-selected among all teams. The second section con-tained questions concerning team context, team composition, team process,and team outcomes. Students were asked to respond to each of these ques-tions in each of two contexts: their best team experience and their worst teamexperience. Students provided responses to each question in a best experi-ence and a worst experience column. To clearly identify these teams in theminds of the students, students were asked to write in the course name corre-sponding to their best team experience and their worst team experience at thetop of the respective column. The third section of the questionnaire, whichwas not used for the research presented here, asked the student to rate his orher skills in each of seven areas. The final section of the questionnaire con-tained demographic questions.

A pretest survey was conducted to determine which process variableswould be most relevant to our MBA student population. Although the focusof this study is on contextual variables, a small set of process measures wastaken to gain insight into the effect of contextual variables on outcomes. Inour pretest, a large set of potential process variable items was compiled usingpublished sources on group process and on social loafing. The pretest instru-ment consisted of 58 items. Students were asked to rate the importance ofeach item to have a good team. Data were collected from 52 MBA students intwo classes. The 6 items that were rated most highly were included in the finalinstrument.

SAMPLE

The survey was administered in class. Roughly half of the classes sur-veyed were sections of a first-year MBA course, and the other half were sec-tions of a class taken by students in their second year. Among the 116 respon-dents, the median age was 27, and the median years of full-time workexperience was 4. Of our sample, 44% were women and 18% were interna-tional students.

Results

We first conducted some preliminary analyses to better understand whichfactors were associated with the students’best and worst team experiences—




in other words, how they defined these experiences for themselves. We thenproceeded to test our hypotheses and perform additional analyses to gain adeeper understanding of our findings.

PRELIMINARY RESULTS

Students were asked to indicate which team was their best experience, andwhich was their worst (more specifically, which class was associated withtheir best and worst). We deliberately left “best team” undefined so that wemight later gain insight into what outcomes students associated with theirbest and worst teams. A summary of these outcomes is shown in Table 1. Wedisplay the effect size in the table so that the reader can more clearly discernwhich measures differed the greatest across best and worst teams. The effectsize essentially controls for differences in the scale and variance of the items(note that letter grade does not use the same scale as the other items), provid-ing an indicator of the difference between best and worst teams scaled in stan-dard deviation units.2 All effects are fairly substantial, and some are huge.Kirk (1982) has suggested that for a comparison of means, an effect size of .2should be considered on the small side, whereas an effect size of .8 should beconsidered large (see also J. Cohen, 1992). The effect sizes may have beeninflated slightly by our data collection methodology. Respondents may haveexperienced a contrast effect in rating their best and worst teams, or perhapssome post hoc rationalization, exaggerating any differences between them.Still, by reporting effect size, we can accurately see the relative effects ofthese variables.

As can be seen in the table, the students’enjoyment of the team experienceand their subjective perception of the team’s performance were the moststriking differences across best and worst teams. The students’ letter gradesdiffered significantly across these experiences, but not as much as their ownperception of their performance. Contrary to the adage about learning a lotfrom bad team experiences, our students indicated that they learned moreabout the course material and about teamwork from their best team experi-ences than from their worst.

Table 2 offers some insight into how group composition and process dif-fers across best and worst teams. As can be seen in the table, items associatedwith social loafing differed dramatically across best and worst teams. Amongthe team composition items, teams where all members were consideredindispensable and all brought valuable skills to the team had the strongesteffect on best/worst categorization. Among the process items, teams whereall members cooperated and felt accountability for group success and whereno members slacked off had the strongest effect on best/worst categorization.




Interestingly, having an effective team leader did not seem to have as strongan effect as many of the other variables shown in the table, although the effectwas still statistically significant and moderate in size by Kirk’s (1982)standards.

TESTS OF HYPOTHESES

We next examine how contextual variables differ across the best and worstteams. We tested our hypotheses using pairedt tests. The results are shown inTable 3. As can be seen in the table, of our nine hypotheses, four are sup-ported, four are not, and one hypothesis is contradicted. Self-selected teamsare positively linked to best team experiences (Hypothesis 1a). Although ran-dom assignment (Hypothesis 1b) was negatively associated with best teams,this relationship was not significant. Team longevity was also significantlyassociated with best teams (Hypothesis 2), indicating that teams that aretogether longer have a better chance of success. Hypotheses 7a and 7b wereboth supported. Improved descriptions of exactly what the students wererequired to submit or present (description of outcome, Hypothesis 7a) had astronger effect at .46 than did improved descriptions of how the group shouldperform team tasks (description of process, Hypothesis 7b) at .33. Theweight given the team grade (Hypothesis 3), the team size (Hypothesis 5),and the presence of management training (Hypothesis 6) all had no relation-ship with best/worst team experiences. Interestingly, the use of peer evalua-tions was negatively associated with best teams, reversing Hypothesis 4.


TABLE 1Outcome Differences Across the Best and Worst Team Experiences

Outcome Item Mean for Best Mean for Worst EffectDescription Experience Experience Size

I enjoyed the team experience. 4.32 2.10 1.85***The team performed very well. 4.57 2.43 1.74***What letter grade did the team receive on theproject (or average grade on the projects, e.g.,A+, A, A–, B+, etc.)? 3.80 3.36 .96***

I learned a lot about the course material. 4.10 2.88 .84***I learned a lot about teamwork. 3.71 2.92 .64***I enjoyed the course itself. 3.75 3.00 .46***

NOTE: A = 4.0. All means are computed from data rated on a 5-point scale ranging from 1(strongly disagree) to 5 (strongly agree), except where noted. Items are sorted by effect size.***p ≤ .001, two-tailed.



Multivariate analyses were then performed to test our hypotheses morerigorously. Because our study was not a true experimental design, some ofour independent variables were correlated. For example, ratings of the qual-ity of the instructor’s descriptions of outcomes and descriptions of processeswere correlated at .53 (n= 229,p ≤ .01), and self-selection was negativelyassociated with peer evaluation (r= –.34,n = 213,p ≤ .01). To control forthese covariances, we performed a multivariate analysis, using all hypothe-sized correlates of best/worst teams simultaneously to predict whether a teamwas more likely to be a best team or a worst team. The use of a dichotomousdependent variable (best/worst) in this analysis necessitated the use of logis-tic regression. The overall model was significant,χ2(4) = 32.56,p= .000, andthe significance of individual coefficients closely paralleled thet testsreported earlier. Once insignificant variables were dropped from the model(p ≥ .10), Hypothesis 1a (p= .075), Hypothesis 2 (p= .001), and Hypothesis


TABLE 2Composition and Process Differences

Across Best and Worst Team Experiences

Mean for Best Mean for Worst EffectExperience Experience Size

Team composition item descriptionEach team member was indispensable. 3.68 1.89 1.17***Each team member had about the samelevel of ability. 3.60 2.29 .76***

Each team member brought a valuable skillto the team. 4.13 2.46 1.16***

There was no difficulty finding a time whenall could meet. 3.36 2.41 .64***

The team had an effective leader. 3.27 2.43 .65***Process item description

All team members had about the same influenceon team decisions. 4.04 2.30 1.11***

Team members completed their work on time. 4.11 2.39 1.19***Team members identified clear goals andobjectives. 3.94 2.46 1.13***

Team members cooperated well with each other. 4.50 2.57 1.37***All team members felt accountability for groupsuccess. 4.39 2.46 1.32***

No one slacked off, getting others to do mostof the work. 4.15 2.22 1.26***

NOTE: All means are computed from data rated on a 5-point scale ranging from 1 (strongly dis-agree) to 5 (strongly agree).***p ≤ .001, two-tailed.



7a (p = .000) were again supported, whereas Hypothesis 4 (p = .044) wasagain reversed. Hypothesis 7b was not supported in this analysis. However,as we noted, student ratings of the descriptions they received about outcomes(Hypothesis 7a) were highly correlated with their ratings of the descriptionsabout processes (Hypothesis 7b). Thus, in a multivariate model, perhaps onlyone of these two hypotheses would be statistically significant, but we suspectthat both are important for team success. Of the two, thet tests and logitanalysis suggest that the description of outcomes has a greater impact onteam experiences than does the description of processes.

In the multivariate model, the findings regarding Hypothesis 1a (self-selection) were not as strongly supported as they were in thet tests. We exam-ined the effect of the method of assignment more carefully in exploratoryanalyses. We might expect that during the first quarter of the MBA program,self-selection and random assignment would lead to similar outcomesbecause the students do not know each other well and have no historytogether. We therefore rerant tests and the logit analysis excluding all teamexperiences from the first quarter of the MBA program. Even with the 34%reduction in effective sample size, the best teams were found to be muchmore likely to be self-selected (75%) than the worst teams (51%),t(150.5) =3.18,p = .001, and the best teams were much less likely to be randomlyassigned (14%) than the worst teams (29%),t(146.3) = 2.31,p = .011. In thelogit analysis, the significance of the effect of self-selection increased fromp=.075 top= .011, whereas the effect of random assignment remained insignifi-cant (p = .33) when first quarter teams were dropped from the analysis.


TABLE 3Tests of Hypotheses Regarding Contextual Differences

Mean for Best Mean for Worst EffectHypothesis Description Experience Experience Size

1a Students self-selected teams 59% 41% .23**1b Students randomly assigned to teams 21% 28% .122 Team longevity (weeks) 6.9 5.5 .36***3 Percentage of course grade on project 30% 32% .174 Use of peer evaluations 58% 74% .22*5 Team size 4.1 4.3 .096 Management education 54% 49% .087a Description of desired outcome 3.71 2.97 .46***7b Description of desired process 2.79 2.37 .33***

*p ≤ .05. **p ≤ .01. ***p ≤ .001, one-tailed.



Although self-selection and random assignment were correlated atr = –.68,the data suggest that self-selection helps more than random assignment hurts.

ADDITIONAL ANALYSES

Although the goal of the present research has been to identify which con-textual variables are associated with good team experiences, we asked a fewteam composition and team process questions to gain some insight into howthese contextual variables affect student teams. To explore the effects of con-textual variables on team composition and process, we first combined theobservations of approximately 116 best and 116 worst team experiences toform a data set of approximately 232 teams. Then, in 11 separate regressions,we regressed each of the five team composition variables and six teamprocess variables on the nine variables associated with our nine hypotheses.The standardized beta coefficients resulting from this analysis, shown inTable 4, indicate which contextual variables affected which composition andprocess variables. All coefficients shown were significant at the .05 level orless. The columns for random assignment, team size, and percentage ofcourse grade on project were dropped because none of the coefficients corre-sponding to these variables was significant.

As can be seen in Table 4, many of the regression coefficients achieve sta-tistical significance even though the contrast effect mentioned earlier mayhave led to the somewhat low adjustedr squares. When best and worst teamsare compared statistically, the contrast effect increases the effect size; butwhen best and worst teams are combined, the contrast effect creates addi-tional error variance, decreasing the effect size, or in regression, leading tolower r squares and lower standardized betas (standardized betas are analo-gous to the effect sizes studied earlier).

As we would expect, the description of team process was substantiallyrelated to all of the process variables, when the process variables were treatedas dependent variables. Thus, the teacher’s guidance with process helped withprocess while guidance on outcomes helped with outcomes (Hypothesis 7a).

Discussion and Recommendations

We offer six recommendations that follow from our findings.

1. Provide teams with adequate descriptions of outcomes and processes.One of the strongest findings from this research is perhaps the easiest to imple-ment: Give students a good description of what you want. An adequatedescription of outcomes (exactly what the student is required to submit or




TABLE 4Standardized Coefficients From Team Composition and Process Variables Regressed on Contextual Variables

Self- Peer Management Outcome ProcessAdjustedR2 Selected Longevity Evaluation Education Described Described

Team compositionEach team member was indispensable. .16*** .29*** .25*** .29***Each team member had about the same level of ability. .12*** .27*** –.17 .16 .16Each team member brought a valuable skill to the team. .11*** .17 .26*** .23**There was no difficulty finding a time when all could meet. .10*** .21** .19** .20**The team had an effective leader. .12*** .18 .31***

Team processAll team members had about the same influence onteam decisions. .16*** .24*** .24*** –.16 .22***

Team members completed their work on time. .15*** .28*** .26*** .24***Team members identified clear goals and objectives. .20*** .21** .29*** –.15 .30***Team members cooperated well with each other. .14*** .28*** .24*** .28***All team members felt accountability for group success. .20*** .18 .26*** –.16 .33***No one slacked off, getting others to do most of the work. .16*** .21** .25*** .16 .20

NOTE: All coefficients shown are significant atp ≤ .05.**p ≤ .01. ***p ≤ .001, two-tailed.

480

at TE

XA

S S

OU

TH

ER

N U

NIV

ER

SIT

Y on N

ovember 18, 2014

jme.sagepub.com

Dow

nloaded from


present) is strongly associated with best team experiences, whereas an ade-quate description of process is strongly associated with improved teamprocesses. Give students not only a clear description of the assignment butalso a clear indication of how the assignment will be evaluated (e.g., adetailed grading sheet). These descriptions should be made available to stu-dents in writing, so that they may have them to refer to as they discuss theassignment in their teams. In some cases, we have allowed students access toreports from previous quarters, so that they can see what other teams havedone. This approach may be effective when assigning projects that are fairlyunique, such as industry analyses or marketing research reports. Unfortu-nately, we feel that we cannot show the instructors’ comments or grades onprojects, as this may violate confidentiality, so the “clean copies” of reportshave limited demonstration value. For projects that may lead to very similarwrite-ups (such as cases), we have experimented with providing a mockwrite-up (created by the faculty) with comments for the first case. The firstcase was assigned to the class as “discussion only,” so there is little concernabout plagiarism.

It is important to note that part of the educational experience may entaillearning to set one’s goals and objectives, and that when teachers specify out-comes too narrowly, creativity may be constrained. However, there is animportant distinction to be drawn between narrow assignment parametersand vague directions and/or desired outcomes. An instructor can clearlyspecify the criteria on which students will be evaluated as well as the range ofpossible forms the assignment may take without compromising creativity(this may even be facilitated by allowing students to determine the weightsgiven to various assignment criteria). The mistake is to be unclear whenexplaining the project and then to be very rigid in evaluating the outcome.Unclear directions may cause students to spend much of their time trying todetermine what it is the instructor expects rather than focusing on doing thework.

2. Maximize team longevity. Team longevity was found to be linked withbest team experiences and with better team processes. We recommend thatteams be assigned as early as possible and that they be given team tasks assoon as possible, perhaps with early assignments to be submitted. It thenbecomes imperative to provide timely feedback about the quality of the workand recommendations for how the team can improve. To gain the most fromthe team experience, team tasks should be designed so that the team contin-ues to work together until the end of the term.




3. Once students know each other, let them have a say in team assign-ments. Self-selection was associated with best team experiences and withimproved team processes. The positive effects of self-selection were morenoticeable after the students’ first term in the program. We note in particularthat self-selected teams rate their cooperativeness and the indispensability oftheir members highly, and self-selected members were more likely to com-plete their work on time. All these factors seem to suggest that among self-selected teams, there are preestablished behavioral norms and commitmentto the group. We suspect that these findings reflect the existence of what wecall “meta-teams,” social networks of students who choose to work togetherin several classes throughout their MBA studies. Members of these meta-teams interact more frequently and thus have more time to establish groupnorms. Often, poor team players are not reselected by other members of themeta-team. Thus, the meta-team effectively punishes undesirable behaviors,enforcing established group norms. The existence of meta-teams, their codesof conduct, and social structure provide an interesting area for futureresearch. Baldwin, Bedell, and Johnson (1997) provide an important firststep in this area by developing a methodology for mapping the social networkwithin an MBA program. They note that students who are better connected inthe network tend to perform better in the program. We suspect that efforts toenhance the formation of meta-teams, which may include increased socialinteraction among MBA students (e.g., through social events), or increasedface/name identification (e.g., through the publication of an MBA yearbook),may lead to better team experiences for all students.

However, it should be noted that ongoing self-selected teams run a greaterrisk of experiencing groupthink (Janus, 1982), a team process phenomenonthat can afflict highly cohesive teams. Teams are caught in the quagmire ofgroupthink when the team’s desire to maintain unanimity and team solidarityis so great that it impairs effective decision-making processes. Specifically,team members quickly embrace a decision alternative that is viewed as theteam’s position and disregard other alternatives and ignore any informationthat is contrary to the team’s position. Inadequate information search andevaluation and inefficient alternative development and assessment prevail.The frequency of groupthink among highly cohesive teams is unknown as thephenomenon has been inadequately researched. However, the theory’s stand-ing in the group literature merits training team members in decision-makingprocedures (e.g., mechanisms for information search and alternative genera-tion and evaluation such as devil’s advocacy) to impede the possible emer-gence of groupthink.

With this problem in mind, and to offer the greatest chance for success foreach team, we combine our findings with the findings from previous studies




to suggest that some form of constrained self-selection be employed (Mello,1993). For example, in keeping with Bacon et al.’s (1998) recommendationsabout nationality diversity, students may be allowed to select their own teamsas long as each team has at least one international student and one domesticstudent. Additional team composition goals may be accomplished simulta-neously using a software program developed by the authors that assigns stu-dents to teams. This “Team Maker” program involves the instructor adminis-tering a short questionnaire to all students to determine student demographics,their preferences for teammates, and the roles students would like to play intheir teams. The program then makes team assignments that attempt to simul-taneously satisfy the instructor’s desire for a balance of roles and demograph-ics on each team with student preferences concerning who they want to workwith. Further information on this program is available from the authors.

4. Be wary of the use of traditional peer evaluations. Contrary to commonwisdom and previous research, the use of traditional peer evaluations wasfound to be negatively associated with good team experiences. From Table 4,it appears that these peer evaluations have a negative effect on the tendencyfor team members to have equal influence, the team’s ability to agree ongoals, and each member’s felt accountability. In the presence of peer evalua-tions, team members may also be more likely to view others as having differ-ent abilities than their own. It thus appears that the use of end-of-the-quarter,private peer evaluation may actually encourage undesirable behaviors. Whenpoor team dynamics occur during the quarter, rather than confront each otherand seek to resolve unproductive conflict, students may tolerate this conflictthinking that they can “burn” those they are in conflict with at the end of thequarter on the peer evaluations. Thus, although students may feel that justiceis done, team process and performance is actually undermined. This finding isconsistent with earlier research (Strong & Anderson, 1990), which found peerevaluations to be the least effective tool for improving team performance.

At this point, we recommend that instructors not follow the traditionalpeer evaluation process alone, although we are uncertain of which evaluationmethod is clearly superior, given the paucity of research. Methods thatinvolve frequent, open feedback among members may be helpful. As a feed-back mechanism, traditional peer evaluation is inconsistent with Harrisonand Cooper’s (1976) observation that “individuals do not learn from randomexperience. They learn by bringing out essential patterns of thought andbehavior in a situation where they can receive clear and accurate informationabout the relevancy and effectiveness of their work” (p. 266). However, theinstructor must be aware that too much emphasis on individual performancemay undermine team performance. Another approach would be to eliminate




peer evaluation altogether, but offer teams the option to fire uncooperative orunproductive members. In Strong and Anderson’s (1990) study, studentsrated the firing option as more effective in motivating team members thanpeer evaluations.

5.Set teamsizebypedagogicalobjectives.We foundno relationshipbetweenteam size and best or worst team experiences or team processes. This may bebecause we did not control for project size in this study. We suspect that forsome projects a group size of five is too small, whereas for others a size ofthree is too many. Bacon et al. (1998) report on a student team project whereteam sizes in excess of two offered no improvements in team performance;Wolfe and Chacko (1983) found that performance peaked in their businesssimulation with a team size of three; and Rollier (1992) recommended fourfor his business simulation teams. We recommend that the instructor care-fully examine the pedagogical goals for each team project. The instructorshould ask himself or herself, “Do I want all students to master all skills, orwill I be content if only some students master some skills?” The size of theteam may then be determined by the number of unique skills that will not berequired of all team members. For example, simulations involve roles such asfinance vice president, marketing vice president, or operations vice presi-dent. Teams may be assigned with enough players to fill the roles but no extra.The instructor should also ask, “Is one goal of the team project to developteam skills, and if so, which team skills?” We have heard of teams involvingas many as 12 students, and these students are asked to produce a businessplan in 48 hours. Clearly, one goal of this experience is to develop skills incoordinating a large group of people. Once the pedagogical objectives of theteam are identified, the team size should be set at the smallest number reason-able for accomplishing these objectives. Larger sizes simply allow studentsto become less active in the learning process. As discussed earlier, the peda-gogical objectives should also shed some light on the degree of interdepend-ence that a group task requires, and as Wageman (1995) has suggested, thenature of the group task should be matched to the reward system (e.g., group vs.individual).

6. Look for ways to improve team training. It was not surprising to see thatthe management education our students received was not associated witheither best or worst team experiences. A number of issues are relevant here.First, the management education our MBAs receive includes a broad range oftopics, such as organizational effectiveness, motivation and performance,leadership, politics, culture, and so forth. Because successful performance on




class assignments requires students to demonstrate understanding of each ofthese topics, the emphasis placed on learning about teams may be diluted.Second, even when the specific topic has to do with teams, the focus is on theunderstanding of team dynamics and factors that contribute to team effective-ness, rather than on developing team skills and building effective teamprocesses. Third, our students receive team training only in the first course inthe MBA curriculum, and little effort is made to building on this training insubsequent courses.

A couple of recommendations may help the management training we giveour students improve their team experiences. First, enhance team trainingwith team-building activities. French & Bell (1994) suggest that team-building activities can be focused on a number of critical areas includingproblem solving, decision making, goal setting, role clarification, and inter-personal relationships. A second recommendation is to reinforce this trainingthrough the entire MBA program. Many experts suggest that effective teambuilding can take up to 5 years (French & Bell, 1994).

A third set of recommendations has specifically to do with improvingteam training in a classroom setting. Rentsch, Heffner, & Duffy (1994) sug-gest that people’s experience with teams is a critical factor in structuring teamtraining. Team members with less experience will first need to acquire essen-tial facts about teamwork, whereas more experienced team members maylearn best from experiential training in which they apply their teamworkknowledge to different team situations. Jones (1996) suggests that instructorscan improve the likelihood of a successful team-based learning approach bytraining students in group dynamics, developing a system of accountabilityand responsibility, and encouraging team interaction through required teammeetings.

Conclusion

One of the most important findings of this research warrants reiterationhere: Students learn more about teams from good team experiences than theydo from bad ones (see Table 1). This finding admonishes us as teachers toplace students in team situations that have the greatest chance for success.Although we cannot ensure the success of every team, by offering writteninstructions for the teams, maximizing team longevity, giving students a sayin team assignments, avoiding the traditional peer evaluation process, match-ing the team size to the pedagogical objectives, and finding ways to improveteam training, we can establish an environment that is most likely to lead togood team experiences.




Notes

1. We recognize that many student groups are not truly teams, but instead can be more aptlydescribed as work groups (Katzenbach & Smith, 1993). For simplicity, we use the wordteamthroughout to refer to teams and work groups.

2. Different statistical tests are associated with different measures of effect size (J. Cohen,1992). We use pairedt tests extensively in this article, and so compute effect size as the meanwithin-subject difference divided by the standard deviation of the difference.

References

Albanese, R., & Van Fleet, D. D. (1985). Rational behavior in groups: The free-riding tendency.Academy of Management Review, 10(2), 244-255.

Bacon, D. R., Stewart, K. A., & Stewart-Belle, S. (1998). Exploring predictors of student teamproject performance.Journal of Marketing Education,20(1), 63-71.

Baldwin, T. T., Bedell, M. D., & Johnson, J. L. (1997). The social fabric of a team-based M.B.A.program: Network effects on student satisfaction and performance.Academy of Manage-ment Journal, 40(6), 1369-1397.

Bettenhausen, K. L. (1991, June). Five years of group research: What we have learned and whatneeds to be addressed.Journal of Management, 345-381.

Burningham, C., & West, M. A. (1995). Individual, climate, and group interaction processes aspredictors of work team innovation.Small Group Research,26(1), 106-117.

Clark, G. L. (1989, Fall). Peer evaluations: An empirical test of their validity and reliability.Journal of Marketing Education,11, 41-58.

Cohen, A. R. (1993).The portable MBA in management. New York: Wiley.Cohen, J. (1992). A power primer.Psychological Bulletin,112(1), 155-159.Comer, D. R. (1995). A model of social loafing in real work groups.Human Relations,48(6),

647-667.Cook, R. W. (1981). An investigation of student peer evaluation on group project performance.

Journal of Marketing Education,3(1), 50-52.Decker, R. (1995). Management team formation for large scale simulations. In J. D. Overby &

A. L. Patz (Eds.),Developments in business simulation & experiential exercises (22)(pp.128-129). Statesboro, GA: Association for Business Simulation and Experiential Learning.

Eden, D. (1985). Team development: A true field experiment at three levels of rigor.Journal ofApplied Psychology, 70(1), 94-100.

Fisher, C. D., Shaw, J. B., & Ryder, P. (1994). Problems in project groups: An anticipatory casestudy.Journal of Management Education,18(3), 351-355.

Fowler, A. (1995). How to build effective teams.People Management,1(4), 40-41.French, W. L., & Bell, C. H. (1994).Organizational development: Behavioral science interven-

tions for organizational improvement. Englewood Cliffs, NJ: Prentice Hall.Gentry, J. W. (1980). Group size and attitudes toward the simulation experience.Simulation &

Games,11(4), 451-459.Gersick, C.J.G. (1989). Marking time: Predictable transitions in task groups.Academy of Man-

agement Journal,32(2), 274-309.Gosenpud, J. J., & Washbush, J. B. (1991). Predicting simulation performance: Differences

between individuals and groups. In W. J. Wheatley & J. Gosenpud (Eds.),Developments in




business simulation & experiential exercises (18)(pp. 44-48). Stillwater, OK: Associationfor Business Simulation and Experiential Learning.

Hackman, J. R. (Ed.) (1990).Groups that work (and those that don’t). San Francisco: Jossey-Bass.

Harkins, S. G., & Jackson, J. M. (1985). The role of evaluation in eliminating social loafing.Per-sonality and Social Psychology Bulletin,11(4), 457-465.

Harrison, K., & Cooper, C. L. (1976). The use of groups in education.Small Group Behavior,7(3), 259-270.

Ingham, A. G., Levinger, G., Graves, J., & Peckham, V. (1974). The Ringelmann effect: Studiesof group size and group performance.Journal of Experimental Social Psychology, 10,371-384.

Jaffe, E. D., & Nebenzahl, I. D. (1990). Group interaction and business game performance.Simulation & Gaming, 21(2), 133-146.

Jalajas, D. S., & Sutton, R. I. (1984-1985). Feuds in student groups, coping with whiners, mar-tyrs, saboteurs, bullies, and deadbeats.Organizational Behavior Teaching Review, 9(4),217-227.

Janus, I. L. (1982).Groupthink(2nd ed.). Boston: Houghton-Mifflin.Jones, D. W. (1996). Empowered teams in the classroom can work.Journal for Quality and Par-

ticipation,19, 80-87.Katz, R. (1982). The effects of group longevity on project communication and performance.

Administrative Science Quarterly, 27(1), 81-104.Katzenbach, J. R., & Smith, D. K. (1993). The discipline of teams.Harvard Business Review,

71(2), 111-120.Kerr, N. L. (1983). Motivation losses in small groups: A social dilemma analysis.Journal of Per-

sonality and Social Psychology, 45(4), 819-828.Kerr, N. L., & Bruun, S. E. (1983). Dispensability of member effort and group motivation losses:

Free-rider effects.Journal of Personality and Social Psychology, 44(1), 78-94.Kirk, R. E. (1982).Experimental design: Procedures for the behavioral sciences(2nd ed.). Bel-

mont, CA: Brooks/Cole.Krayer, K. J. (1988). Exploring group maturity in the classroom.Small Group Behavior, 19(2),

259-272.Latané, B., Williams, K., & Harkins, S. (1979). Many hands make light the work: The causes and

consequences of social loafing.Journal of Personality and Social Psychology, 37(6),822-832.

Lerner, L. D. (1995). Making student groups work.Journal of Management Education,19(1),123-125.

LeRosen, R. G. (1976, April). Group projects, peer rating scales: Management education tools.Journal of Business Education, 317-318.

Mello, J. A. (1993). Improving individual member accountability in small work group settings.Journal of Management Education,17(2), 253-259.

Mesch, D. J. (1991). The jigsaw technique: A way to establish individual accountability in groupwork. Journal of Management Education,15(3), 355-358.

Michaelsen, L. K. (1991). From the editor.Journal of Management Education,15(3), 275.Quirk, T. (1989, Spring). A procedure designed to assist students to improve their presentation

skills as part of a marketing planning team.Journal of Marketing Education,11, 40-44.Rentsch, J. R., Heffner, T. S., & Duffy, L. T. (1994). What you know is what you get from experi-

ence: Team experience related to teamwork schemas.Group & Organization Management,19, 450-475.




Rollier, B. (1992). Observations of a corporate facilitator.Simulation & Gaming, 23(4),442-456.

Rosenbaum, M. E., Moore, D. I., Cotton, J. L., Cook, M. S., Hieser, R. A., Shovar, M. N., & Gray,M. J. (1980). Group productivity and process: Pure and mixed reward structures and taskinterdependence.Journal of Personality and Social Psychology, 39, 626-642.

Schultz, B., & Anderson, J. (1984). Training in the management of conflict.Small Group Behav-ior, 15(3), 333-348.

Steers, R. M., & Porter, L. W. (1991).Motivation and work behavior(5th ed.). New York:McGraw-Hill.

Strong, J. T., & Anderson, R. E. (1990, Summer). Free-riding in group projects: Control mecha-nisms and preliminary data.Journal of Marketing Education,12, 61-67.

Tuckman, B. W. (1965). Developmental sequence in small groups.Psychological Bulletin,63,384-389.

Vora, J. A., & Akula, W. G. (1978). Peer and self assessments in small groups.Small GroupBehavior, 9(3), 427-434.

Wageman, R. (1995). Interdependence and group effectiveness.Administrative Science Quar-terly, 40(1), 145-180.

Williams, D. L., Beard, J. D., & Rymer, J. (1991, Summer). Team projects: Achieving their fullpotential.Journal of Marketing Education,13, 45-53.

Witteman, H. (1991). Group member satisfaction.Small Group Research,22(1), 24-58.Wolfe, J., & Box, T. M. (1988). Team cohesion effects on business game performance.Simula-

tion & Games,19(1), 82-98.Wolfe, J., & Chacko, T. I. (1983). Team-size effects on business game performance and

decision-making behaviors.Decision Sciences,14, 121-133.Zemke, R. (1993). Rethinking the rush to team up.Training, 30(11), 55-61.




lessons from the best and worst student team experiences: how a teacher can make the difference

Documents